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Record W7132961406

Exploring the professional world: Lessons i have learned at my workplace.

2024· other· en· W7132961406 on OpenAlexaboutno aff
María Camila Álvarez Beltrán

Bibliographic record

VenueBiblioteca Digital Universidad de Cartagena · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsInternshipMultinational corporationWork (physics)Closing (real estate)Customer serviceService (business)Professional developmentBest practice
DOInot available

Abstract

fetched live from OpenAlex

University internships are crucial for academic and professional development. In this work, I reflect on my experiences during this period, exploring lessons learned and challenges overcome. From the classroom to the field, every moment has been an opportunity to grow and discover the professional world. This work represents the closing of an academic cycle and the beginning of a new phase of professional development. My case might be a bit different from my peers since I am validating my workplace as my university internship, which has presented significant challenges for me. I am working at Servicios Logísticos Cartagena S.A.S, where we support our parent company, Katoen Natie. Katoen Natie is a multinational company of Belgian origin, primarily focused on supporting large multinational companies with the transportation and storage of their products. The mission of the company is simple: creating maximum added value. Katoen Natie achieves this by providing tailor-made, full-service logistics and engineering solutions to a key number of customers worldwide. Currently, our four offices are located in the Torre del Puerto building in Manga, with around 70 people working towards the same goal: Providing the best customer service possible. In SLC, we primarily focus on providing support to our Katoen Natie warehouses in the United States and Canada, acting as data processors—the "front line" receiving our clients' requests. To provide a bit more context, the logistics sector of the United States is advanced and complex, supported by extensive transportation infrastructure, cutting-edge technology, and comprehensive services. Regarding my goals when starting to work at the company, my main objective was to learn more about the logistics sector, as it has always been where I wanted to work as a professional. It is a highly competitive sector not only locally but also internationally. Additionally, I was very curious to learn about the types of systems and databases (such as SAP and PLATO) that large companies use to track all movements of their products. This kind of knowledge makes me a more well-rounded and prepared professional while enriching my resume at the same time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0250.034
Scholarly communication0.0280.026
Open science0.0050.022
Research integrity0.0090.028
Insufficient payload (model declined to judge)0.0060.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.088
GPT teacher head0.313
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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